State Feedback Control and Kalman Filtering with MATLAB/Simulink Tutorials [Bookshelf]

The book situates itself in a unique niche “between proportional-integral-derivative (PID) and model predictive control (MPC),” as a compromise between the tradeoffs and advantages of each. The book emphasizes state-space techniques but goes beyond the standard presentation of these ideas to consider their application in more traditional industrial settings, where consideration must be given to MIMO dynamics, regulation and setpoint tracking, disturbance rejection, integrator windup, and more. The book shows how to adapt the modern state-space approach to deal with these more classical concepts. At the same time, these adaptations are combined with the state-space design concepts of linear quadratic regulation (LQR) and state estimation through observers and Kalman filters. Readers of the book are thus left with a toolbox that, while not going all of the way to a full MPC framework, marries the practical design consideration of classical control to the power of state-space methods for optimal design of MIMO systems. The book also has an associated companion website for instructors where the MATLAB files and nominal lecture slides can be found. The book's conversational style and ample use of examples make the material easy to understand. Further, it uses a novel approach to introduce integrator-based compensation with antiwindup considerations into state feedback controller design. The book is also valuable in its careful discussion of discrete time implementation of controllers, including the generalization of integrator-based compensation to full internal model control. Finally, the book provides a great introduction to the theory and use of Kalman filters. I would certainly recommend this book as a basis for a second course in control focused on teaching the design of state-space controllers.